Composed Chart By Category X
Build mixed charts from categorical data with multiple series, separate Y axes, and per-series chart type selection for section reporting
Specs
Version
0.1.0 (updated on 2026-05-18)
Developer
Labii Inc.
Type
Section
Support Configuration
Yes
Overview
The Composed Chart By Category X widget visualizes categorical laboratory data with a mix of chart styles in a single section widget. It lets you configure multiple numeric series, assign each series its own chart type, color, aggregation rule, and left or right Y axis, then plot them against the same categorical X axis. This makes the widget well suited for comparing measurements with different units or display needs, such as counts, yields, percentages, and concentrations, without splitting the analysis into separate charts.
Use Cases
Multi-Metric Experiment Review: Show sample count as bars, average yield as a line, and impurity percentage as an area series across treatment groups
Manufacturing Batch Monitoring: Compare batch volume, pass rate, and defect count in one view while keeping incompatible units on separate Y axes
Quality Control Dashboards: Overlay maximum, average, and minimum values for grouped categories such as lots, instruments, or operators
Inventory and Consumption Tracking: Plot item usage with bars and remaining stock with a line across reagent categories or storage locations
Project Reporting: Summarize throughput, turnaround time, and exception rate across teams or workflow stages in one composed visualization
Grouped Scientific Analysis: Break each numeric series into separate traces by group so researchers can compare responses by condition, species, or site
Interface
Read-only View
The read-only view displays a composed chart where all configured series share the same categorical X axis while each series can render as a bar, line, area, or scatter trace. The chart is optimized for comparison across categories and is especially useful when different metrics need distinct visual treatments.
Data Display: Categorical values appear on the X axis, with one or more numeric series rendered together in a single chart
Mixed Visualization: Each series can use a different chart type, helping users distinguish counts, trends, and distributions at a glance
Dual Y Axes: Series can be assigned to the left or right Y axis to compare measurements with different scales or units
Series Differentiation: Colors and legends help identify each series and grouped variation
Interactive Review: Hovering over the chart reveals exact values for each visible series at a category
Export Access: The widget supports downloading the data behind the chart for further analysis
Edit View
The edit view is not applicable for this widget. Composed Chart By Category X is a reporting widget, so users configure it through the widget settings panel rather than editing the chart directly inside the section body.
Configuration
Initial Setup
Add the Composed Chart By Category X widget to a section from the Data Driven Charts category
Open the widget settings by clicking the Configure button in the widget header
Select the source table, define the X axis, then add one or more numeric series for the composed chart
Adjust sorting, grouping, axis assignments, and auto-update settings, then click Save
Required Settings
Table: Select a table to update the filter dropdown and define the dataset used by the widget
Optional Settings
Data Source and Filtering
Query: Specify a query to limit the results included in the chart. Use this to focus the widget on a subset of records such as a single project, date range, or status
X Axis Settings
X axis: Choose a column for the X axis. If nothing is selected, the record name is used as the category label
X axis sorting: Choose how to sort X axis values
String (A-Z): Sort alphabetically in ascending order
String (Z-A): Sort alphabetically in descending order
Number (Ascending): Sort numerically in ascending order
Number (Descending): Sort numerically in descending order
RID (Ascending): Sort by record ID in ascending order
RID (Descending): Sort by record ID in descending order
X axis format: Choose how foreign key values appear on the X axis
Full (UID: Name): Display the full foreign key label
Name only: Display only the referenced record name
Grouping
Group: Choose a column to group data by. Group values become separate chart series for each configured numeric series, which is useful when you want to compare the same measurement across conditions or cohorts
Series Configuration
Series: Add one or more series. Each series can use its own column, chart type, color, Y axis, and aggregation method
Series > Column: Choose a numeric column for the series
Series > Chart type: Choose how the series is drawn
Area: Emphasize magnitude and fill beneath the trend
Bar: Compare discrete category values clearly
Line: Highlight trend changes across categories
Scatter: Emphasize individual points rather than connected trends
Series > Color: Set the display color for the series
Series > Y axis: Choose whether the series uses the left or right Y axis
Left: Plot the series against the primary Y axis
Right: Plot the series against the secondary Y axis
Series > Data aggregation: Define how values are summarized when multiple records match the same X axis value
Aggregation Options
The widget supports the following aggregation values for each series:
None: Show values without aggregation when the data structure allows it
Sum: Add matching values together
Max: Return the largest value
Median: Return the middle value
Min: Return the smallest value
Average: Return the mean value
Display Settings
Chart title: Provide the title shown above the chart
Height: Set chart height in pixels. The default is 250px
Auto-Update Settings
Should auto update: If enabled, the widget performs a live recalculation when source data changes
Should auto update when empty: If enabled, the widget performs a live calculation even when the widget is currently empty
Choose the Table that contains the records you want to visualize
Select an X axis column, or leave it empty to use record names
Optionally set Query, X axis sorting, X axis format, and Group to shape the dataset and category presentation
Add one or more Series, then configure the numeric Column, Chart type, Color, Y axis, and Data aggregation for each series
Set the Chart title, adjust Height, and enable either auto-update option if the chart should refresh automatically
Click Save to render the composed chart
This widget is most effective when each configured series represents a meaningful numeric measure and the chosen X axis has a manageable number of categories.
Advanced Configuration
For more analytical layouts:
Assign low-range metrics such as percentages to the Right Y axis and high-range metrics such as counts or totals to the Left Y axis
Mix Bar, Line, Area, and Scatter series to distinguish totals, trends, envelopes, and point-based measurements in one chart
Use Group together with multiple configured series when you need each measurement split by condition, instrument, or treatment group
Apply Query filters to narrow the chart to a specific project phase, sample class, time window, or QC status when performance or readability becomes an issue
Too many categories, groups, or series can make the chart difficult to read. If the visualization becomes crowded, reduce the scope with a query or split the analysis across multiple widgets.
Additional Functions
Mixed Series Visualization
The primary strength of this widget is its ability to combine different chart types in one chart.
Bar series are useful for totals, counts, or category-level comparisons
Line series are useful for trends or continuous movement across ordered categories
Area series help emphasize magnitude or coverage
Scatter series highlight individual values or sparse distributions
This flexibility helps laboratories present several related measures together without forcing them into a single chart style.
Separate Y Axes
Each configured series can be assigned to a different Y axis.
Use the Left axis for primary metrics such as totals, counts, or concentration
Use the Right axis for secondary metrics such as percentage, rate, or normalized score
This is especially useful when the same categorical X axis needs to compare values with very different scales.
Grouped Output
When a Group column is configured, the widget creates separate chart traces for each group value within each numeric series. This supports deeper comparisons such as:
treatment versus control within each assay metric
operator comparison across the same production measure
species or site comparison across multiple calculated outputs
Data Export
Users can download the chart data for external reporting or advanced analysis.
Open the widget in read-only mode after the chart has rendered
Click the Download button available with the widget
Save the exported data for use in spreadsheet tools, presentations, or statistical software
Auto-Update Behavior
With auto-update enabled, the widget can refresh itself as records change in the source table. This supports live monitoring use cases such as ongoing sample intake, test result accumulation, or production tracking.
Use auto-update for operational dashboards or actively changing sections, and disable it for static review pages where recalculation is not necessary.
Best Practices
Design the Chart Around the Decision
Use bars for straightforward category comparison, lines for trends, areas for emphasis, and scatter points for discrete observations
Reserve the second Y axis for genuinely different units or scales rather than for visual decoration
Keep chart titles specific so readers understand the scientific or operational question being answered
Keep Series Intentional
Add only the series that support the current analysis question
Choose colors with strong contrast so overlapping series remain distinguishable
Prefer consistent aggregation logic when series are meant to be compared directly
Control Complexity
Limit the number of visible categories when possible to preserve readability
Use Query and Group carefully, since combining both with many series can create a crowded legend and dense chart area
Split very complex reporting needs into multiple widgets instead of forcing all measures into one visualization
Validate the Source Data
Ensure each series uses numeric columns with reliable units and definitions
Confirm foreign key formatting choices on the X axis match how users identify referenced records
Review aggregation choices so the summary reflects the intended laboratory meaning, especially for averages, medians, and maxima
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